This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. We have debugged a stochastic simulation of genetic evolution of the influenza A virus (IVA). The purpose of the model is to a construct a realistic model to seed the introduction of specific viral strains in US-wide population models currently run as part of the Pitt MIDAS project (Burke et al.). The model considers three pools of genetic material (birds, swine and humans), with genetic evolution occurring in all pools. Some strains will get transmitted between pools, thus introducing new strains in humans. The code is written in Fortran95. Our current single-run time on a workstation is about 48 hours as we wish to simulate evolution over about 40 years. Since we need to calibrate the model to data, we wish to conduct a large number (>10000 if possible) of shorter (5-7 years) runs to construct realistic parameter sets. Runs would initially be run independently. Thus the initial need is for a distributed platform, without shared memory requirement. We are developing the software for an MPI implementation to support adaptive parameter learning- but this is not ready for prime time yet.